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TPDI · ARI — Market Rankings & OTA Dominance

TPDI lists 263 analyses across 58 cities. Average dependence score: 79/100. Average ARI: 49/100.

Global Overview of Analyzed Tourism Markets

The global overview aggregates all published TPDI analyses. It shows the total number of markets analyzed, the number of cities and countries covered, and the average structural dependence score across the dataset.

Markets Analyzed

263

Cities

58

Global Average Score

79 / 100

Global ARI Average

49 / 100

Actor Distribution

Local Operators1087
Resellers1639
Platforms3556
DMO84
Editorial48

Booking Signals

Direct Booking951
Platform (OTA)5063
Contact Only277
No Signal Detected123

The global distribution reflects the current state of tourism market digitization. Markets with high dependence scores show strong reliance on online travel agencies and remote resellers for visibility and booking completion. Markets with lower scores show more direct booking presence. The trend varies by region, destination maturity, and activity type. As the dataset grows, the global overview provides a baseline for understanding structural patterns in tourism markets.

Market Rankings — Platform Dependence & Direct Booking Visibility

Rankings highlight structural imbalances in global tourism markets. High dependence scores indicate strong reliance on online travel agencies and remote resellers. High direct booking visibility indicates more local control over the transaction path. These rankings are based on observed data, not estimates.

Top 10 — Highest Platform Dependence

Top 10 — Strongest Direct Booking Visibility

Top 10 — Best Agentic Readiness (ARI)

Explore TPDI · ARI by Country

Each country aggregates data from its analyzed cities. Country scores reflect the weighted average of observed structures. Variations between countries show differences in digital maturity, market concentration, and booking infrastructure.

Mexico

53 analyses6 cities

Score: 85 / 100

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Portugal

34 analyses3 cities

Score: 79 / 100

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Greece

24 analyses3 cities

Score: 71 / 100

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India

23 analyses9 cities

Score: 82 / 100

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Canada

12 analyses5 cities

Score: 80 / 100

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Belgium

11 analyses2 cities

Score: 84 / 100

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France

8 analyses1 cities

Score: 66 / 100

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Spain

8 analyses1 cities

Score: 68 / 100

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Japan

8 analyses3 cities

Score: 81 / 100

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South Africa

6 analyses1 cities

Score: 83 / 100

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New Zealand

6 analyses1 cities

Score: 69 / 100

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Brazil

5 analyses1 cities

Score: 84 / 100

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Netherlands

5 analyses2 cities

Score: 65 / 100

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Australia

5 analyses1 cities

Score: 59 / 100

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Italy

5 analyses1 cities

Score: 64 / 100

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United States

5 analyses2 cities

Score: 79 / 100

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Peru

5 analyses2 cities

Score: 84 / 100

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Denmark

5 analyses1 cities

Score: 77 / 100

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Indonesia

5 analyses1 cities

Score: 84 / 100

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Morocco

5 analyses1 cities

Score: 74 / 100

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Nepal

5 analyses1 cities

Score: 82 / 100

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Norway

4 analyses2 cities

Score: 70 / 100

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Cambodia

4 analyses1 cities

Score: 90 / 100

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Kenya

2 analyses1 cities

Score: 87 / 100

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Philippines

2 analyses1 cities

Score: 83 / 100

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Vietnam

2 analyses1 cities

Score: 92 / 100

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Switzerland

2 analyses1 cities

Score: 81 / 100

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Sweden

2 analyses1 cities

Score: 89 / 100

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Maldives

1 analyses1 cities

Score: 74 / 100

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Iran

1 analyses1 cities

Score: 87 / 100

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What TPDI · ARI Measures

TPDI · ARI is a structural measurement framework that observes how local tourism markets depend on online travel agencies, booking platforms, and remote resellers for visibility and transaction completion. It does not measure market share or revenue. It measures observable digital structure.

Tourism platform dependence refers to the extent to which a destination's visible offers rely on third-party booking infrastructure. When dependence is high, online travel agency dominance shapes how consumers discover and book. When it is low, direct booking visibility prevails. The index quantifies this structural reality across cities and activities.

A TPDI score between 0 and 100 indicates the proportion of visible offers in a given market that rely on intermediary infrastructure to complete bookings. A score of 0 means all observed offers use direct booking infrastructure. A score of 100 means all observed offers route through platforms or remote resellers. The score reflects structural exposure, not consumer preference or business performance.

OTA dominance in a market means that a large share of visible offers depends on online travel agencies and remote resellers to capture attention and finalize transactions. Booking platform reliance varies by region: some destinations show strong direct booking presence, others show heavy intermediary concentration. The index captures these differences without judging them.

Strong OTA dependence has implications for local operators. When visibility and booking control are mediated by intermediaries, commission exposure and dependence on third-party algorithms increase. Online travel agency dependency affects how revenue flows through the local economy. The index does not prescribe solutions; it documents structure.

The TPDI distinguishes between visibility structure and booking structure. Visibility structure answers: who occupies the most visible digital space? Local operators, remote resellers, or platforms? Booking structure answers: how are transactions finalized? Direct booking, platform-only, contact-only, or no detectable signal? Both dimensions matter. A market can have high local operator visibility but low direct booking visibility if those operators rely on platforms for checkout.

Direct booking visibility is a key indicator because it reflects how much of the offer is directly bookable by the consumer without intermediaries. When direct booking visibility is low, the market structure is more dependent on third-party infrastructure. When it is high, local operators retain more control over the transaction path. Intermediary dominance in tourism markets often correlates with commission leakage: revenue that leaves the local circuit when bookings route through platforms.

Platforms dominate certain markets because of network effects, brand recognition, and consumer habits. When a destination is heavily marketed through OTAs, the digital landscape becomes more concentrated. The TPDI captures this structural concentration without implying causality. Tourism market structure varies by activity type: accommodation, guided experiences, and signature local activities each show different patterns.

Local economic impact varies. High dependence scores suggest structural exposure to commission leakage. Low scores suggest more direct control. The index is a measurement tool; it does not prescribe policy or strategy. Policymakers, operators, and researchers can use the data to understand digital market structure and inform decisions.

The economic impact of OTA dependence manifests in how revenue circulates locally. When a large share of visible bookings routes through online travel agencies, commission leakage affects the local economy. Tourism commissions flow to intermediaries rather than remaining in the destination. This structural exposure varies by market; the index quantifies it without estimating absolute amounts.

Digital concentration in tourism markets shapes discovery and booking. When a few platforms dominate visibility, the market structure becomes more dependent on intermediary algorithms. Digital intermediaries condition how offers appear to consumers. The index captures this concentration by measuring the proportion of visible offers that rely on platform or reseller infrastructure.

Structural effects on direct booking are significant. When direct booking visibility is low, local operators lose control over the transaction path. They depend on third-party infrastructure for both visibility and checkout. The reverse holds when direct booking visibility is high: operators retain more control. Platform dominance in tourism markets correlates with reduced operator autonomy over pricing, customer data, and the booking experience.

What is the Agentic Readiness Index (ARI)?

The ARI measures how prepared a tourism market is to be discovered, evaluated, and booked by AI travel agents — autonomous systems that research and transact on behalf of travelers. A high ARI score indicates that local offers are structured, directly bookable, and machine-readable. A low score indicates structural friction: missing booking signals, heavy intermediary dependence, or low local operator visibility.

ARI scores range from 0 to 100. They are calculated alongside each TPDI analysis and reflect the same observed data from a different angle: not how dependent a market is on platforms, but how ready it is for what comes next.

Full ARI methodology

Why Measure Platform Dependence?

Measuring tourism platform dependence provides a macro lens on how digital markets are structured. The indicator is relevant because it documents observable reality rather than intent. It answers a simple question: in a given market, what proportion of visible offers relies on intermediary infrastructure to complete bookings?

Understanding tourism market structure is essential for policymakers, destination managers, and operators. The index makes structural patterns comparable across cities, countries, and activities. It does not measure performance or quality; it measures digital structure. This comparability supports informed debate about platform dominance, commission leakage, and direct booking strategies.

International comparability is built into the methodology. Each market follows the same analytical framework. Scores can be compared across destinations because the measurement criteria are identical. The index thus serves as a structural benchmark for global tourism markets.

Economic Impact

The economic impact of OTA dependence manifests in how revenue circulates locally. When a large share of visible bookings routes through online travel agencies, commission leakage affects the local economy. Tourism commissions flow to intermediaries rather than remaining in the destination. This structural exposure varies by market; the index quantifies it without estimating absolute amounts.

Structural effects on direct booking are significant. When direct booking visibility is low, local operators lose control over the transaction path. They depend on third-party infrastructure for both visibility and checkout. The reverse holds when direct booking visibility is high: operators retain more control. Platform dominance in tourism markets correlates with reduced operator autonomy over pricing, customer data, and the booking experience.

Digital Concentration

Digital concentration in tourism markets shapes discovery and booking. When a few platforms dominate visibility, the market structure becomes more dependent on intermediary algorithms. Digital intermediaries condition how offers appear to consumers. The index captures this concentration by measuring the proportion of visible offers that rely on platform or reseller infrastructure.

Methodological Framework

The TPDI uses a standardized framework. Each market is defined by country, city, activity, and differentiating criterion. Data collection examines the most visible digital offers at the time of observation. Actors are classified as local operators, remote resellers, or platforms. Booking signals are classified as direct, platform-only, contact-only, or none. The index measures structural visibility, not total inventory. It does not capture offline sales, private contracts, or customer satisfaction. Scores update dynamically as new analyses are published.

Full methodology

How to Interpret the TPDI Score

A score of 0–30 indicates low dependence: a majority of visible offers use direct booking infrastructure. A score of 30–60 indicates moderate dependence: mixed structures with significant intermediary presence. A score of 60–80 indicates high dependence: a large share of visible offers routes through platforms or resellers. A score of 80–100 indicates structural dominance: most visible offers rely on intermediary infrastructure for transactions. The score is descriptive, not predictive.